Tahamina Yesmin, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.12, December- 2024, pg. 35-46 © 2024, IJCSMC All Rights Reserved, ZAIN Publicatons, Fridhemsgatan 62, 112 46, Stockholm, Sweden 35 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 7.056 IJCSMC, Vol. 13, Issue. 12, December 2024, pg.35 – 46 AI and ML Technologies Application for Improvement of Renewable Energy Systems: A Review Tahamina Yesmin Adamas University, Kolkata, INDIA ytahamina@gmail.com DOI: https://doi.org/10.47760/ijcsmc.2024.v13i12.004 Abstract: An extremely useable and excellent alternate power source is solar power which can really reduce or it may say cut our dependency on the non-renewable energy sources and destructive fossil fuels. Solar radiation energy source has an important role in various platforms like climate and weather extremes, photosynthesis, hydrological cycles, balancing the radiation and geographic conditions etc that is why it has very important role in solar energy. Solar radiation (SR) can be anticipated with extraordinary accuracy, and it could be feasible to definitely limit the effect cost related with the advancement of solar energy. This study aims to research different machine learning applications — regarding different instinctive forecast benchmark models from the writing audits to anticipate the improvement of Renewable Energy Frameworks. The applications utilized to the various models to control, or to anticipate exhibitions of the energy frameworks are muddled including differential conditions, enormous PC power, and time necessities. Machine Learning strategies give off an impression of being perhaps of the strongest candidates. The paper gives an outline of generally involved AI philosophies in solar energy, with a unique accentuation on Artificial Brain Organization. Keywords: AI, Solar, Radiation, Renewable, Energy, Review.